{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load water level data from DMI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\JAN\\AppData\\Local\\Temp/ipykernel_21332/396824514.py:3: DeprecationWarning: `set_matplotlib_formats` is deprecated since IPython 7.23, directly use `matplotlib_inline.backend_inline.set_matplotlib_formats()`\n",
      "  set_matplotlib_formats('png')\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import set_matplotlib_formats\n",
    "set_matplotlib_formats('png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tsod.detectors import CombinedDetector, RangeDetector, DiffDetector, RollingStandardDeviationDetector\n",
    "from tsod.hampel import HampelDetector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = os.path.join(\"..\", \"tests\", \"data\", \"Ballen_20150218-20201222.csv\")\n",
    "df = pd.read_csv(file_path, index_col=0, parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = df.water_level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Detect anomalies outside manually set range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_anomalies = RangeDetector(-1, 1.3).detect(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Anomalies detected: 1254'}>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "detected = data.to_frame()\n",
    "detected[\"anomalies\"] = data[range_anomalies.values]\n",
    "detected.plot(style=['-', 'o'], figsize=(8,3), title=f\"Anomalies detected: {range_anomalies.sum()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_clean = data.copy()\n",
    "data_clean[range_anomalies.values] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Detect anomalies outside automatically set range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 1000\n",
    "normal_data, test_data = data[:N], data[N:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "anomaly_detector = CombinedDetector([RangeDetector(), DiffDetector()])\n",
    "anomaly_detector.fit(normal_data)\n",
    "detected_anomalies = anomaly_detector.detect(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2015-02-25 12:30:00    False\n",
       "2015-02-25 12:40:00    False\n",
       "2015-02-25 12:50:00    False\n",
       "2015-02-25 13:00:00    False\n",
       "2015-02-25 13:20:00    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "detected_anomalies.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Detect peaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "detector = RollingStandardDeviationDetector(10, 0.1)\n",
    "std_anomalies = detector.detect(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "detected = data.to_frame()\n",
    "detected[\"anomalies\"] = data[std_anomalies.values]\n",
    "detected.plot(style=['-', 'o'], figsize=(8,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hampel filter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The default threshold of the HampelDetector is 3, which means that a sample that deviates by more than three times of the rolling window's standard deviation is marked as an anomaly. **Increasing** the threshold marks **more** samples as anomalies, **decreasing** the threshold marks **fewer**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "detector = HampelDetector(window_size=20, threshold=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "anomalies = detector.detect(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Anomalies detected: 287'}>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "detected = data.to_frame()\n",
    "detected[\"anomalies\"] = data[anomalies]\n",
    "detected.plot(style=['-', 'o'], figsize=(8,3), title=f'Anomalies detected: {sum(anomalies)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
